| Autor: |
Grieve, Andrew P., Sarker, Shah‐Jalal |
| Předmět: |
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| Zdroj: |
Pharmaceutical Statistics; Nov/Dec2016, Vol. 15 Issue 6, p507-516, 10p |
| Abstrakt: |
There have been many approximations developed for sample sizing of a logistic regression model with a single normally-distributed stimulus. Despite this, it has been recognised that there is no consensus as to the best method. In pharmaceutical drug development, simulation provides a powerful tool to characterise the operating characteristics of complex adaptive designs and is an ideal method for determining the sample size for such a problem. In this paper, we address some issues associated with applying simulation to determine the sample size for a given power in the context of logistic regression. These include efficient methods for evaluating the convolution of a logistic function and a normal density and an efficient heuristic approach to searching for the appropriate sample size. We illustrate our approach with three case studies. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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